Stochastic frontier estimation through parametric modelling of quantile regression coefficients
نویسندگان
چکیده
Abstract Stochastic frontiers are a very popular tool used to compare production units in terms of efficiency. The parameters this class models usually estimated through the use classic maximum likelihood method even, last years, some authors suggested conceive and estimate productive frontier within quantile regression framework. main advantages approach lie weaker assumptions about data distribution greater robustness presence outliers respect approach. However, empirical evidence theoretical contributions have highlighted that applied tails conditional distribution, namely frontiers, suffers from instability estimates needs specific tools approaches. To avoid limitation, we propose model stochastic as function order smooth its trend and, consequently, reduce instability. has been illustrated using real simulated experiments confirming good efficiency properties proposed method.
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ژورنال
عنوان ژورنال: Empirical Economics
سال: 2022
ISSN: ['1435-8921', '0377-7332']
DOI: https://doi.org/10.1007/s00181-022-02273-x